Grid Resource Management: State of the Art and Future TrendsJarek Nabrzyski, Jennifer M. Schopf, Jan Weglarz Springer Science & Business Media, 06.12.2012 - 575 Seiten Grid Resource Management: State of the Art and Future Trends presents an overview of the state of the field and describes both the real experiences and the current research available today. Grid computing is a rapidly developing and changing field, involving the shared and coordinated use of dynamic, multi-institutional resources. Grid resource management is the process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring Grid resources over time in order to run Grid applications as efficiently as possible. While Grids have become almost commonplace, the use of good Grid resource management tools is far from ubiquitous because of the many open issues of the field, including the multiple layers of schedulers, the lack of control over resources, the fact that resources are shared, and that users and administrators have conflicting performance goals. These are the issues addressed in this book, in addition to elucidating the overlap with related areas including discussions of work with peer-to-peer computing, economic approaches, and operations research. Grid Resource Management: State of the Art and Future Trends is an invaluable resource for today's user, application developer, or resource owners when working with Grid resource management systems. |
Inhalt
3 | |
Application Requirements for Resource Brokering in a Grid Environment 25 | 24 |
Attributes for Communication Between Grid Scheduling Instances | 41 |
6 | 71 |
Workflow Management in GriPhyN | 99 |
8 | 119 |
Karl Czajkowski Ian Foster Carl Kesselman and Steven Tuecke | 135 |
11 | 161 |
18 | 271 |
20 | 320 |
21 | 341 |
Computation Scheduling and Data Replication Algorithms for Data Grids | 359 |
23 | 377 |
24 | 395 |
25 | 412 |
26 | 431 |
13 | 177 |
14 | 192 |
Using Predicted Variance for Conservative Scheduling on Shared Resources | 215 |
Schopf and Lingyun Yang | 231 |
17 | 244 |
27 | 447 |
28 | 464 |
References | 507 |
567 | |
Andere Ausgaben - Alle anzeigen
Grid Resource Management: State of the Art and Future Trends Jarek Nabrzyski,Jennifer M. Schopf,Jan Weglarz Eingeschränkte Leseprobe - 2004 |
Grid Resource Management: State of the Art and Future Trends Jarek Nabrzyski,Jennifer M. Schopf,Jan Weglarz Keine Leseprobe verfügbar - 2012 |
Häufige Begriffe und Wortgruppen
allocation approach architecture attributes bandwidth bandwidth brokers brokering cache Carl Kesselman Chapter checkpointing ClassAds client components computational resources Computer Science Condor configuration CPU load decision defined described disk distributed computing domain dynamic evaluate example execution Figure files framework function GARA global Global Grid Forum Globus Toolkit Grid applications Grid computing Grid environment Grid resource management Grid scheduler Grid Services GridFTP Ian Foster implementation infrastructure input interface job scheduling JXTA layer Legion machine management system Maui metaheuristics metascheduling middleware monitoring multicriteria multiple NeST nodes object OGSA operating P2P systems parameters peer performance Platform LSF prediction problem processors protocol queue replication request requirements scenario scheduling algorithms scheduling instance Section sensor server service path simulation solution space specified storage subjob task techniques tion Triana workflow workload